Title
Bilinear spatiotemporal basis models
Abstract
A variety of dynamic objects, such as faces, bodies, and cloth, are represented in computer graphics as a collection of moving spatial landmarks. Spatiotemporal data is inherent in a number of graphics applications including animation, simulation, and object and camera tracking. The principal modes of variation in the spatial geometry of objects are typically modeled using dimensionality reduction techniques, while concurrently, trajectory representations like splines and autoregressive models are widely used to exploit the temporal regularity of deformation. In this article, we present the bilinear spatiotemporal basis as a model that simultaneously exploits spatial and temporal regularity while maintaining the ability to generalize well to new sequences. This factorization allows the use of analytical, predefined functions to represent temporal variation (e.g., B-Splines or the Discrete Cosine Transform) resulting in efficient model representation and estimation. The model can be interpreted as representing the data as a linear combination of spatiotemporal sequences consisting of shape modes oscillating over time at key frequencies. We apply the bilinear model to natural spatiotemporal phenomena, including face, body, and cloth motion data, and compare it in terms of compaction, generalization ability, predictive precision, and efficiency to existing models. We demonstrate the application of the model to a number of graphics tasks including labeling, gap-filling, denoising, and motion touch-up.
Year
DOI
Venue
2012
10.1145/2159516.2159523
ACM Trans. Graph.
Keywords
Field
DocType
bilinear spatiotemporal basis model,spatiotemporal sequence,cloth motion data,bilinear spatiotemporal basis,temporal regularity,efficient model representation,bilinear model,autoregressive model,spatiotemporal data,natural spatiotemporal phenomenon,computer graphics
Computer vision,Motion capture,Artificial intelligence,GRAP,Computer graphics,Mathematics,Bilinear interpolation
Journal
Volume
Issue
ISSN
31
2
0730-0301
Citations 
PageRank 
References 
46
1.56
43
Authors
5
Name
Order
Citations
PageRank
Ijaz Akhter12488.27
Tomas Simon222213.27
Sohaib Khan362434.83
Iain Matthews44900253.61
Yaser Sheikh5211892.13